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PURPOSE: Data are limited on sodium glucose co-transport 2 inhibitors (SGLT2-is) and glucagon-like peptide-1 receptor agonists (GLP-1 RAs) among real-world cohorts of underrepresented patients. We examined these therapies and glycemic control in US adults with diabetes mellitus (DM) by atherosclerotic cardiovascular disease (ASCVD) risk and sociodemographic factors. METHODS: In the NIH Precision Medicine Initiative All of Us Research Program, we categorized DM as (1) moderate risk, (2) high risk, and (3) with ASCVD. We examined proportions on DM therapies, including SGLT2-i or GLP-1 RA, and at glycemic control by sociodemographic factors and CVD risk groups. RESULTS: Our 81,332 adults aged ≥ 18 years with DM across 340 US sites included 22.3% non-Hispanic Black, 17.2% Hispanic, and 1.8% Asian participants; 31.1%, 30.3%, and 38.6% were at moderate risk, high risk, or with ASCVD, respectively. Those with DM and ASCVD were most likely on SGLT2-i (8.6%) or GLP-1 RA (11.9%). SGLT2-i use was < 10% in those with heart failure or chronic kidney disease. The odds (95% CI) of SGLT2-i use were greater among men (1.35 [1.20, 1.53]) and Asian persons (2.31 [1.78, 2.96]), with GLP-1 RA being less common (0.78 [0.70, 0.86]) in men. GLP-1 RA use was greater among those with health insurance, and both GLP-1 RA and SGLT2-i greater within lower income groups. 72.0% of participants had HbA1c < 7%; Hispanic persons were least likely at glycemic control. CONCLUSIONS: Treatment with SGLT2-is and GLP-1 RAs remains low, even among higher ASCVD risk persons with DM and use is even lower among underserved groups.
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Objective: To assess and characterize online ratings and comments on laryngologists and determine factors that correlate with higher ratings. Methods: All the American Laryngological Association (ALA) members were queried across several online platforms. Ratings were normalized for comparison on a five-point Likert scale. Ratings were categorized based on context and for positive/negative aspects. Results: Of the 331 ALA members, 256 (77%) were rated on at least one online platform. Across all platforms, the average overall rating was 4.39 ± 0.61 (range: 1.00-5.00). Specific positive ratings including "bedside manners," "diagnostic accuracy," "adequate time spent with patient," "appropriate follow-up," and "physician timeliness" had significant positive correlations to overall ratings, by Pearson's correlation (P < 0.001). Long wait times had significant negative correlations to overall ratings (P < 0.001). Conclusion: Online ratings and comments for laryngologists are significantly influenced by patient perceptions of bedside manner, physician competence, and time spent with the patient.
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Real-world data on lipid levels and treatment among adults with diabetes mellitus (DM) are relatively limited. We studied lipid levels and treatment status in patients with DM across cardiovascular disease (CVD) risk groups and sociodemographic factors. In the All of Us Research Program, we categorized DM as (1) moderate risk (≤1 CVD risk factor), (2) high risk (≥2 CVD risk factors), and (3) DM with atherosclerotic CVD (ASCVD). We examined the use of statin and non-statin therapy as well as LDL-C and triglyceride levels. We studied 81,332 participants with DM, which included 22.3% non-Hispanic Black and 17.2% Hispanic. A total of 31.1% had ≤1 DM risk factor, 30.3% had ≥2 DM risk factors, and 38.6% of participants had DM with ASCVD. Only 18.2% of those with DM and ASCVD were on high-intensity statins. Overall, 5.1% were using ezetimibe and 0.6% PCSK9 inhibitors. Among those with DM and ASCVD, only 21.1% had LDL-C < 70 mg/dL. Overall, 1.9% of participants with triglycerides ≥ 150 mg/dL were on icosapent ethyl. Those with DM and ASCVD were more likely to be on high-intensity statins, ezetimibe, and icosapent ethyl. Guideline-recommended use of high-intensity statins and non-statin therapy among our higher risk DM patients is lacking, with LDL-C inadequately controlled.
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Objective: Tinnitus is defined as the perception of sound in the absence of an external source. We propose the hypothesis that migraine can cause exacerbation of tinnitus in some patients. Methods: English literature from PubMed has been reviewed. Results: Studies have reported a high prevalence of cochlear symptoms in patients with migraine headaches and up to 45% of tinnitus patients have been shown to concomitantly suffer from migraine. Both conditions are thought to stem from central nervous system disturbances, involving disruption of the auditory and trigeminal nerve pathways. One proposed mechanism of this association is the modulation of sound sensitivity by trigeminal nerve activation of the auditory cortex during migraine attacks, resulting in tinnitus fluctuation in some patients. Increased brain and inner ear vascular permeability resulting from trigeminal nerve inflammation, can also cause observed headache and auditory symptoms. Tinnitus and migraine also share a number of symptom triggers including stress, sleep disturbances, and dietary factors. These shared features may help explain promising results of migraine therapies for the treatment of tinnitus. Conclusion: Given the complex association between tinnitus and migraine, further investigation is needed to identify the underlying mechanisms and determine the optimal treatment strategies for managing migraine-related tinnitus patients.
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The development of public health education campaigns about tobacco products requires an understanding of specific audience segments including their views, intentions, use of media, perceived barriers, and benefits of change. For example, identifying and targeting individuals who express ambivalence about e-cigarette use on Twitter may be helpful in devising and focusing public health campaigns to reduce e-cigarette use. This study developed a novel analytic strategy using social network analysis to identify audience segments on Twitter based on positive, negative, and neutral e-cigarette sentiment. Using Twitter data collected from April 2015 to March 2016, we identified different sub-groups of users who retweeted about e-cigarettes, and measured each sub-group's clustering coefficient (CC), which describes how tightly people cluster together. Ten high CC and ten low CC groups were randomly selected; then 100 randomly selected tweets from each group were coded for e-cigarette sentiment (positive, negative, neutral). Results indicate that differences in e-cigarette sentiment are associated with clustering of Twitter network ties. Statistical analyses revealed that high CC groups were more likely to have strong e-cigarette sentiments, suggesting that tightly clustered groups may be "echo chambers" (i.e., like-minded people repeating the same messages). By contrast, low CC groups were more likely to have neutral sentiments, and had greater fluctuation in sentiment over time, suggesting that they may be more flexible in their opinions about e-cigarettes and may be particularly receptive to targeted public health campaigns. Informatics techniques such as determination of clusters using social network analysis can be useful in identifying audience segments for future public health campaigns.